{"id":"https://openalex.org/W4296501491","doi":"https://doi.org/10.1109/access.2022.3208147","title":"Deep Label Feature Fusion Hashing for Cross-Modal Retrieval","display_name":"Deep Label Feature Fusion Hashing for Cross-Modal Retrieval","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4296501491","doi":"https://doi.org/10.1109/access.2022.3208147"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3208147","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3208147","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09895402.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09895402.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003115287","display_name":"Dongxiao Ren","orcid":"https://orcid.org/0000-0002-5868-1684"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongxiao Ren","raw_affiliation_strings":["School of Science, Zhejiang University of Science and Technology, Hangzhou, China","School of Science, Zhejiang University of Science and Technology, No.318 LiuHe Road, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5868-1684","affiliations":[{"raw_affiliation_string":"School of Science, Zhejiang University of Science and Technology, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]},{"raw_affiliation_string":"School of Science, Zhejiang University of Science and Technology, No.318 LiuHe Road, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690857","display_name":"Weihua Xu","orcid":"https://orcid.org/0000-0003-4257-8508"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Xu","raw_affiliation_strings":["School of Science, Zhejiang University of Science and Technology, Hangzhou, China","School of Science, Zhejiang University of Science and Technology, No.318 LiuHe Road, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4257-8508","affiliations":[{"raw_affiliation_string":"School of Science, Zhejiang University of Science and Technology, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]},{"raw_affiliation_string":"School of Science, Zhejiang University of Science and Technology, No.318 LiuHe Road, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100726998","display_name":"Zhonghua Wang","orcid":"https://orcid.org/0000-0002-1370-482X"},"institutions":[{"id":"https://openalex.org/I4210127555","display_name":"China Guodian Corporation (China)","ror":"https://ror.org/02zrmae98","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210127555"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhonghua Wang","raw_affiliation_strings":["Beijing Guodiantong Network Technology Company Ltd., Beijing, China","Beijing GuoDianTong Network Technology Co., Ltd, Building 32, ChuangYe Middle Road, Haidian District, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Guodiantong Network Technology Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210127555"]},{"raw_affiliation_string":"Beijing GuoDianTong Network Technology Co., Ltd, Building 32, ChuangYe Middle Road, Haidian District, Beijing, China","institution_ids":["https://openalex.org/I4210127555"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073280180","display_name":"Qinxiu Sun","orcid":"https://orcid.org/0000-0002-5188-3873"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinxiu Sun","raw_affiliation_strings":["School of Science, Zhejiang University of Science and Technology, Hangzhou, China","School of Science, Zhejiang University of Science and Technology, No.318 LiuHe Road, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science, Zhejiang University of Science and Technology, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]},{"raw_affiliation_string":"School of Science, Zhejiang University of Science and Technology, No.318 LiuHe Road, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5003115287"],"corresponding_institution_ids":["https://openalex.org/I168879160"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2032,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.48292345,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"10","issue":null,"first_page":"100276","last_page":"100285"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8193987607955933},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6944928765296936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6103178262710571},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5892339944839478},{"id":"https://openalex.org/keywords/feature-hashing","display_name":"Feature hashing","score":0.5820333361625671},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.547603964805603},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.5398980379104614},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.526191771030426},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5128076672554016},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4634428322315216},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39505669474601746},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.35930925607681274},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.15921610593795776},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.08145633339881897}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8193987607955933},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6944928765296936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6103178262710571},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5892339944839478},{"id":"https://openalex.org/C133667856","wikidata":"https://www.wikidata.org/wiki/Q5439682","display_name":"Feature hashing","level":5,"score":0.5820333361625671},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.547603964805603},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.5398980379104614},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.526191771030426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5128076672554016},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4634428322315216},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39505669474601746},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.35930925607681274},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.15921610593795776},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.08145633339881897},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3208147","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3208147","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09895402.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0c145c93bf8245d3b4fa22069d7f66d2","is_oa":true,"landing_page_url":"https://doaj.org/article/0c145c93bf8245d3b4fa22069d7f66d2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 100276-100285 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3208147","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3208147","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09895402.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G5043067281","display_name":null,"funder_award_id":"11801511","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320311003","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322856","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189"},{"id":"https://openalex.org/F4320322878","display_name":"Henan University","ror":"https://ror.org/003xyzq10"},{"id":"https://openalex.org/F4320322927","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884"},{"id":"https://openalex.org/F4320322951","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/03893we55"},{"id":"https://openalex.org/F4320325434","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4296501491.pdf","grobid_xml":"https://content.openalex.org/works/W4296501491.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1910300841","https://openalex.org/W1922199343","https://openalex.org/W1970055505","https://openalex.org/W1976258951","https://openalex.org/W2006147162","https://openalex.org/W2007972815","https://openalex.org/W2049993534","https://openalex.org/W2086958058","https://openalex.org/W2117539524","https://openalex.org/W2155803963","https://openalex.org/W2203543769","https://openalex.org/W2243225650","https://openalex.org/W2266728343","https://openalex.org/W2388114291","https://openalex.org/W2425857666","https://openalex.org/W2476034201","https://openalex.org/W2604880013","https://openalex.org/W2606965845","https://openalex.org/W2801086478","https://openalex.org/W2911878585","https://openalex.org/W2945524220","https://openalex.org/W2962955826","https://openalex.org/W2963173190","https://openalex.org/W2963187862","https://openalex.org/W2965509144","https://openalex.org/W2967957126","https://openalex.org/W2970487977","https://openalex.org/W3006962461","https://openalex.org/W3014701888","https://openalex.org/W3037158620","https://openalex.org/W3097639209","https://openalex.org/W3104374384","https://openalex.org/W3111773629","https://openalex.org/W3118309101","https://openalex.org/W3124335959","https://openalex.org/W3175888430","https://openalex.org/W3202874825","https://openalex.org/W3211544782","https://openalex.org/W4226172762","https://openalex.org/W4313178921","https://openalex.org/W6608183366","https://openalex.org/W6681077227","https://openalex.org/W6684115544","https://openalex.org/W6684191040","https://openalex.org/W6685282478","https://openalex.org/W6688759320","https://openalex.org/W6721087566","https://openalex.org/W6786686642"],"related_works":["https://openalex.org/W4381744218","https://openalex.org/W2144265691","https://openalex.org/W2059244188","https://openalex.org/W2035647105","https://openalex.org/W1981124010","https://openalex.org/W3192025065","https://openalex.org/W3087964089","https://openalex.org/W4205587245","https://openalex.org/W4211126162","https://openalex.org/W3158263601"],"abstract_inverted_index":{"The":[0,121],"rapid":[1],"growth":[2],"of":[3,41,55,142,181],"multi-modal":[4],"data":[5,18,67,108,132],"in":[6,97,114],"recent":[7],"years":[8],"has":[9,25],"driven":[10],"the":[11,42,53,56,60,69,76,128,135,140,160,176,179,182],"strong":[12],"demand":[13],"for":[14,118],"retrieving":[15],"semantic":[16,62,77,104,129,136],"related":[17],"within":[19],"different":[20,80,115],"modalities.":[21],"Therefore,":[22],"cross-modal":[23,44,85,143,190],"hashing":[24,45,86,93,191],"attracted":[26],"extensive":[27],"interest":[28],"and":[29,37,133,152,175],"studies":[30],"due":[31],"to":[32,51,65,73,157],"its":[33],"fast":[34],"retrieval":[35],"speed":[36],"good":[38],"accuracy.":[39],"Most":[40],"existing":[43],"models":[46],"simply":[47],"apply":[48],"neural":[49],"networks":[50,113,117],"extract":[52],"features":[54,109,123],"original":[57],"data,":[58,82],"ignoring":[59],"unique":[61],"information":[63,106],"attached":[64],"each":[66],"by":[68,110],"labels.":[70],"In":[71,145],"order":[72],"better":[74,187],"capture":[75,127],"correlation":[78,130],"between":[79,131],"modal":[81,116],"a":[83],"novel":[84],"model":[87],"called":[88],"deep":[89],"label":[90,105,112,150,155],"feature":[91,119,149,154],"fusion":[92],"(DLFFH)":[94],"is":[95],"proposed":[96,183],"this":[98],"article.":[99],"We":[100],"can":[101,124],"effectively":[102],"embed":[103],"into":[107],"building":[111],"fusion.":[120],"fused":[122],"more":[125],"accurately":[126],"bridge":[134],"gap,":[137],"thus":[138],"improving":[139],"performance":[141],"retrieval.":[144],"addition,":[146],"we":[147],"construct":[148],"branch":[151],"corresponding":[153],"loss":[156],"ensure":[158],"that":[159],"generated":[161],"hash":[162],"codes":[163],"are":[164],"discriminative.":[165],"Extensive":[166],"experiments":[167],"have":[168],"been":[169],"conducted":[170],"on":[171],"three":[172],"general":[173],"datasets":[174],"results":[177],"demonstrate":[178],"superiority":[180],"DLFFH":[184],"which":[185],"performs":[186],"than":[188],"most":[189],"models.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
